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In this paper, we present a method for affine invariant feature description. Based on the gradient distribution of an image region we calculate two basis vectors defining an affine invariant coordinate system, used to normalize the image region. The estimated basis vectors are non-orthogonal and allow for a precise representation of the gradient distribution. The proposed method can be combined with...
In this paper, we present a method to increase invariance against affine deformations in feature based object detection systems. We use the gradient distribution of an image region to calculate two non-orthogonal basis vectors defining an affine invariant coordinate system, which is used to normalize the image region. The proposed method is an intermediate processing step subsequent to the feature...
In this paper, we present an affine invariant feature descriptor, which is based on the well known Scale Invariant Feature Transform algorithm. The descriptor is a weighted histogram of gradient orientations and invariant against scale, in-plane rotation, stretch and skew. To cover the geometrical distortions introduced by an affine image transformation, we create a suiting, affine transformed coordinate...
Fisher Vectors have shown great capability for visual search. Their main drawback is their high dimensionality. We propose several methods to reduce the size of the Fisher Vectors by applying different preprocessing steps and dimension reduction techniques to SIFT descriptors. Also, we investigate the effects of PCA and DCT transforms employed on SIFT descriptors and the resulting improvement for...
In this paper, we present a method for the detection of objects in a quantized feature space. Quantizing the feature space is a preprocessing step to compact the amount of data in large scale image retrieval and classification applications. A drawback, compared to the use of non-quantized features, is the loss in the ability to precisely detect and localize common objects across the images. Our method...
A novel method for generating a reliable initial surface mesh of the interested scene from a quasi-dense point cloud is presented in this article. Given multiple images taken from different points of view, a robust quasi-dense point cloud is acquired by accumulative triangulation of the potentially matched feature points. In our proposed method, the feature points are detected with Harriscorner and...
In this paper we present a method for the detection of wrong feature correspondences in a local feature based object detection system. Common visual objects in different images share not only similar local features but also a similar spatial layout of their features. We will utilize this fact in order to distinguish between correct and wrong feature correspondences. The spatial feature layout will...
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